testDesktop's starred repositories
Sequence-search
Smith-Waterman algorithm; BLOSUM62; introns/exons; Python
PharmaChain
Blockchain and AI powered predictive pharmaceutical inventory
Smart-Contract-GUI
React, Tronweb, Tronlink application to fetch Smart contract details and interact with smart contracts on TRON blockchain, Main Net, Nile Test Net, Shasta Test Net.
learn-solidity
Learn Solidity Step by Step
IBMDeveloper-recipes
The repo holds Recipes from IBM Developer for user access to the information
Auction-Smart-Contract
Final Assignment for BCDV1016
pairwise-alignment-in-python
Pairwise string alignment in Python (Needleman-Wunsch and Smith-Waterman algorithms)
ECG-noise-reduction
Noise reduction using Boxcar Integrator method for ECG signal
ecg-segmented-beat-modulation-noise-removal
Implementation of the ECG noise removal algorithm using segmented-beat modulation proposed by Agostinelli et al., (2014)
MATLABExperiments
A motley collection of snippets, language idioms, algorithms, puzzles, and exploratory code.
PanTompkinsQRS
A portable, ANSI-C implementation of Pan-Tompkins real-time QRS detection algorithm
SimpleDeepNetToolbox
Simple MATLAB toolbox for deep learning network: Version 1.0.3
deep-learning-from-scratch
『ゼロから作る Deep Learning』(O'Reilly Japan, 2016)
DeepLearnToolbox
Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.
ECG-Arrhythmia-classification
ECG arrhythmia classification using a 2-D convolutional neural network
deim-cur-ecg
This repository contains research code for applying DEIM CUR with incremental QR to synthetic and real ECG data.
ECG-Heartbeat-Classification-seq2seq-model
Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach
rf-ecg-heartbeat-classification
Code used for investigating the use of Random Forests for classifying selected heartbeats features
ECG-Arrhythmia-Classification-using-Artificial-Neural-Network
Classify the arrhythmia heartbeats from the MIT-BIH Arrhythmia Database.
cinc-challenge2017
ECG classification from short single lead segments (Computing in Cardiology Challenge 2017 entry)
msc-stress
MSc Project: Quantifying Stress Pattern. A 9-month individual research project, as a part of my MSc Communication & Signal Processing at Imperial College London. (ECG, HRV, SVM, LSTM, MATLAB)
ECG-Anomaly-Detection-Using-Deep-Learning
Ensemble RNN based neural network for ECG anomaly detection